Overview

Dataset statistics

Number of variables4
Number of observations214
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.5%
Total size in memory7.2 KiB
Average record size in memory34.6 B

Variable types

Text1
Numeric2
Categorical1

Dataset

Description신용보증기금의 B2B 담보 관련 업종별 업체 수 및 보증 잔액을 확인할 수 있습니다 (연1회 제공) 기업간(B2B) 전자상거래 지원서비스 종류 및 지원현황 등에 관한 자료
URLhttps://www.data.go.kr/data/3060343/fileData.do

Alerts

주채무과목명 has constant value ""Constant
Dataset has 1 (0.5%) duplicate rowsDuplicates
업체수 is highly overall correlated with 보증잔액High correlation
보증잔액 is highly overall correlated with 업체수High correlation

Reproduction

Analysis started2023-12-12 11:25:22.521028
Analysis finished2023-12-12 11:25:23.852707
Duration1.33 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종구분
Text

Distinct212
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T20:25:24.089695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length11.78972
Min length5

Characters and Unicode

Total characters2523
Distinct characters229
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique210 ?
Unique (%)98.1%

Sample

1st row1차금속제품도매업
2nd row가구소매업
3rd row가전제품및부품도매업
4th row가전제품소매업
5th row가정용액체연료소매업
ValueCountFrequency (%)
화학섬유직물직조업 2
 
0.9%
화학섬유방적업 2
 
0.9%
자동차중고부품및내장품판매업 1
 
0.5%
의료용품및기타의약관련제품제조업 1
 
0.5%
자동차용신품전기장치제조업 1
 
0.5%
의약품및의료용품소매업 1
 
0.5%
인테리어디자인업 1
 
0.5%
유리및창호도매업 1
 
0.5%
유압기기제조업 1
 
0.5%
육류가공식품도매업 1
 
0.5%
Other values (202) 202
94.4%
2023-12-12T20:25:24.754219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 224
 
8.9%
제 155
 
6.1%
조 116
 
4.6%
기 113
 
4.5%
및 112
 
4.4%
품 96
 
3.8%
매 75
 
3.0%
용 62
 
2.5%
타 59
 
2.3%
도 58
 
2.3%
Other values (219) 1453
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2478
98.2%
Other Punctuation 41
 
1.6%
Decimal Number 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 224
 
9.0%
제 155
 
6.3%
조 116
 
4.7%
기 113
 
4.6%
및 112
 
4.5%
품 96
 
3.9%
매 75
 
3.0%
용 62
 
2.5%
타 59
 
2.4%
도 58
 
2.3%
Other values (217) 1408
56.8%
Other Punctuation
ValueCountFrequency (%)
, 41
100.0%
Decimal Number
ValueCountFrequency (%)
1 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2478
98.2%
Common 45
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 224
 
9.0%
제 155
 
6.3%
조 116
 
4.7%
기 113
 
4.6%
및 112
 
4.5%
품 96
 
3.9%
매 75
 
3.0%
용 62
 
2.5%
타 59
 
2.4%
도 58
 
2.3%
Other values (217) 1408
56.8%
Common
ValueCountFrequency (%)
, 41
91.1%
1 4
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2465
97.7%
ASCII 45
 
1.8%
Compat Jamo 13
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 224
 
9.1%
제 155
 
6.3%
조 116
 
4.7%
기 113
 
4.6%
및 112
 
4.5%
품 96
 
3.9%
매 75
 
3.0%
용 62
 
2.5%
타 59
 
2.4%
도 58
 
2.4%
Other values (216) 1395
56.6%
ASCII
ValueCountFrequency (%)
, 41
91.1%
1 4
 
8.9%
Compat Jamo
ValueCountFrequency (%)
ㆍ 13
100.0%

업체수
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.495327
Minimum1
Maximum592
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T20:25:25.019410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q310
95-th percentile73.05
Maximum592
Range591
Interquartile range (IQR)9

Descriptive statistics

Standard deviation58.072057
Coefficient of variation (CV)3.1398232
Kurtosis53.907588
Mean18.495327
Median Absolute Deviation (MAD)2
Skewness6.6964244
Sum3958
Variance3372.3638
MonotonicityNot monotonic
2023-12-12T20:25:25.282962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
1 72
33.6%
2 32
15.0%
3 21
 
9.8%
8 9
 
4.2%
5 8
 
3.7%
4 8
 
3.7%
6 5
 
2.3%
34 4
 
1.9%
7 4
 
1.9%
11 4
 
1.9%
Other values (35) 47
22.0%
ValueCountFrequency (%)
1 72
33.6%
2 32
15.0%
3 21
 
9.8%
4 8
 
3.7%
5 8
 
3.7%
6 5
 
2.3%
7 4
 
1.9%
8 9
 
4.2%
10 3
 
1.4%
11 4
 
1.9%
ValueCountFrequency (%)
592 1
0.5%
363 1
0.5%
310 1
0.5%
265 1
0.5%
163 1
0.5%
145 1
0.5%
123 1
0.5%
104 1
0.5%
83 2
0.9%
75 1
0.5%

주채무과목명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
B2B담보
214 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowB2B담보
2nd rowB2B담보
3rd rowB2B담보
4th rowB2B담보
5th rowB2B담보

Common Values

ValueCountFrequency (%)
B2B담보 214
100.0%

Length

2023-12-12T20:25:26.006521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:25:26.183172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
b2b담보 214
100.0%

보증잔액
Real number (ℝ)

HIGH CORRELATION 

Distinct153
Distinct (%)71.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.6254927 × 109
Minimum10000000
Maximum4.85629 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T20:25:26.429023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000000
5-th percentile43250000
Q11.8925 × 108
median7.535 × 108
Q33.0175 × 109
95-th percentile2.9133658 × 1010
Maximum4.85629 × 1011
Range4.85619 × 1011
Interquartile range (IQR)2.82825 × 109

Descriptive statistics

Standard deviation3.5955025 × 1010
Coefficient of variation (CV)4.7151085
Kurtosis148.6194
Mean7.6254927 × 109
Median Absolute Deviation (MAD)6.885 × 108
Skewness11.444612
Sum1.6318554 × 1012
Variance1.2927639 × 1021
MonotonicityNot monotonic
2023-12-12T20:25:26.729260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
300000000 10
 
4.7%
50000000 7
 
3.3%
60000000 6
 
2.8%
500000000 5
 
2.3%
1000000000 5
 
2.3%
100000000 4
 
1.9%
600000000 4
 
1.9%
80000000 4
 
1.9%
20000000 4
 
1.9%
150000000 4
 
1.9%
Other values (143) 161
75.2%
ValueCountFrequency (%)
10000000 1
 
0.5%
20000000 4
1.9%
30000000 2
 
0.9%
36000000 1
 
0.5%
40000000 3
1.4%
45000000 1
 
0.5%
50000000 7
3.3%
50150000 1
 
0.5%
60000000 6
2.8%
70000000 1
 
0.5%
ValueCountFrequency (%)
485629000000 1
0.5%
121510000000 1
0.5%
92618200000 1
0.5%
82993400000 1
0.5%
68294960000 1
0.5%
61353268928 1
0.5%
53538000000 1
0.5%
38092000000 1
0.5%
34182000000 1
0.5%
32374500000 1
0.5%

Interactions

2023-12-12T20:25:23.091347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:25:22.772306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:25:23.279704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:25:22.924192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:25:26.901905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체수보증잔액
업체수1.0000.875
보증잔액0.8751.000
2023-12-12T20:25:27.055006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체수보증잔액
업체수1.0000.816
보증잔액0.8161.000

Missing values

2023-12-12T20:25:23.589624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:25:23.794461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

업종구분업체수주채무과목명보증잔액
01차금속제품도매업592B2B담보485629000000
1가구소매업10B2B담보476000000
2가전제품및부품도매업53B2B담보38092000000
3가전제품소매업50B2B담보14127000000
4가정용액체연료소매업1B2B담보300000000
5강관제조업10B2B담보9620000000
6강화및재생목재제조업2B2B담보1600000000
7건물용기계ㆍ장비설치공사업16B2B담보4098000000
8건설ㆍ광업용기계및장비도매업3B2B담보465000000
9계면활성제제조업2B2B담보240000000
업종구분업체수주채무과목명보증잔액
204플라스틱합성피혁제조업1B2B담보150000000
205플라스틱물질및합성고무도매업163B2B담보121510000000
206합성섬유제조업3B2B담보670000000
207합성수지및기타플라스틱물질제조업75B2B담보32374500000
208혼성및재생플라스틱소재물질제조업1B2B담보220000000
209화장품및화장용품도매업1B2B담보500000000
210화학섬유방적업5B2B담보1484000000
211화학섬유직물직조업2B2B담보500000000
212화학섬유방적업3B2B담보1484000000
213화학섬유직물직조업2B2B담보500000000

Duplicate rows

Most frequently occurring

업종구분업체수주채무과목명보증잔액# duplicates
0화학섬유직물직조업2B2B담보5000000002